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Load Forecasting with LSTM and Loss of Life Estimation of Distribution Transformer Considering the Impacts of Electric Vehicle

Publication Type : Conference Paper

Publisher : Springer Nature Singapore

Source : Lecture Notes in Electrical Engineering

Url : https://doi.org/10.1007/978-981-97-2788-9_7

Campus : Coimbatore

School : School of Engineering

Department : Electrical and Electronics

Year : 2024

Abstract : Electric vehicle is becoming an extra load on the existing power grid. Integration of electric vehicle in electrical network increases power quality issues and deterioration of electrical assets like transformer. The increase in load on the electrical system and its impact on electrical assets need to be analyzed properly. Hence, this work focuses on LSTM—a deep learning ANN model-based load forecasting and loss of life (LoL) estimation considering the impact of electric vehicles (EV). The load forecast RMSE for LSTM model is obtained as 0.72411.

Cite this Research Publication : Lekshmi R. Chandran, Nachiket V. Padwal, Manjula G. Nair, K. Ilango, Load Forecasting with LSTM and Loss of Life Estimation of Distribution Transformer Considering the Impacts of Electric Vehicle, Lecture Notes in Electrical Engineering, Springer Nature Singapore, 2024, https://doi.org/10.1007/978-981-97-2788-9_7

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